Overview

Brought to you by YData

Dataset statistics

Number of variables33
Number of observations4749
Missing cells10524
Missing cells (%)6.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory264.0 B

Variable types

Numeric8
Text10
Categorical4
DateTime6
Unsupported5

Alerts

number is highly overall correlated with typeHigh correlation
runtime is highly overall correlated with show_averageRuntimeHigh correlation
season is highly overall correlated with show_typeHigh correlation
show_averageRuntime is highly overall correlated with runtimeHigh correlation
show_id is highly overall correlated with show_weightHigh correlation
show_language is highly overall correlated with show_statusHigh correlation
show_status is highly overall correlated with show_language and 1 other fieldsHigh correlation
show_type is highly overall correlated with season and 1 other fieldsHigh correlation
show_weight is highly overall correlated with show_idHigh correlation
type is highly overall correlated with numberHigh correlation
type is highly imbalanced (96.2%) Imbalance
airtime has 2444 (51.5%) missing values Missing
show_ended has 3039 (64.0%) missing values Missing
show_network has 4233 (89.1%) missing values Missing
show_summary has 779 (16.4%) missing values Missing
id has unique values Unique
url has unique values Unique
links_self has unique values Unique
rating is an unsupported type, check if it needs cleaning or further analysis Unsupported
show_genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
show_rating is an unsupported type, check if it needs cleaning or further analysis Unsupported
show_network is an unsupported type, check if it needs cleaning or further analysis Unsupported
show_links is an unsupported type, check if it needs cleaning or further analysis Unsupported
show_weight has 146 (3.1%) zeros Zeros

Reproduction

Analysis started2024-11-05 04:00:16.665193
Analysis finished2024-11-05 04:00:32.066973
Duration15.4 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

id
Real number (ℝ)

Unique 

Distinct4749
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2768556.9
Minimum2391730
Maximum3044218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:32.242503image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum2391730
5-th percentile2693711
Q12732499
median2744339
Q32777704
95-th percentile2932342.6
Maximum3044218
Range652488
Interquartile range (IQR)45205

Descriptive statistics

Standard deviation71033.732
Coefficient of variation (CV)0.025657314
Kurtosis2.7525054
Mean2768556.9
Median Absolute Deviation (MAD)14591
Skewness1.6071894
Sum1.3147877 × 1010
Variance5.0457911 × 109
MonotonicityNot monotonic
2024-11-04T23:00:32.442932image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2751926 1
 
< 0.1%
2730586 1
 
< 0.1%
2730587 1
 
< 0.1%
2730588 1
 
< 0.1%
2730589 1
 
< 0.1%
2730590 1
 
< 0.1%
2730591 1
 
< 0.1%
2730592 1
 
< 0.1%
2730593 1
 
< 0.1%
2730594 1
 
< 0.1%
Other values (4739) 4739
99.8%
ValueCountFrequency (%)
2391730 1
< 0.1%
2494160 1
< 0.1%
2580338 1
< 0.1%
2580339 1
< 0.1%
2610881 1
< 0.1%
2610882 1
< 0.1%
2625941 1
< 0.1%
2633274 1
< 0.1%
2633275 1
< 0.1%
2633276 1
< 0.1%
ValueCountFrequency (%)
3044218 1
< 0.1%
3044217 1
< 0.1%
3044216 1
< 0.1%
3044215 1
< 0.1%
3044214 1
< 0.1%
3044213 1
< 0.1%
3044212 1
< 0.1%
3044211 1
< 0.1%
3041500 1
< 0.1%
3041499 1
< 0.1%

url
Text

Unique 

Distinct4749
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:32.742492image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length192
Median length147
Mean length79.095178
Min length53

Characters and Unicode

Total characters375623
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4749 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2730586/neznost-2x01-seria-1
2nd rowhttps://www.tvmaze.com/episodes/2730587/neznost-2x02-seria-2
3rd rowhttps://www.tvmaze.com/episodes/2730588/neznost-2x03-seria-3
4th rowhttps://www.tvmaze.com/episodes/2730589/neznost-2x04-seria-4
5th rowhttps://www.tvmaze.com/episodes/2730590/neznost-2x05-seria-5
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2692646/nedetskoe-kino-1x01-seria-1 1
 
< 0.1%
https://www.tvmaze.com/episodes/2751926/the-tonight-show-starring-jimmy-fallon-2024-01-31-arnold-schwarzenegger-kathryn-newton-the-lemon-twigs 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730586/neznost-2x01-seria-1 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730587/neznost-2x02-seria-2 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730588/neznost-2x03-seria-3 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730589/neznost-2x04-seria-4 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730590/neznost-2x05-seria-5 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730591/neznost-2x06-seria-6 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730592/neznost-2x07-seria-7 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730593/neznost-2x08-seria-8 1
 
< 0.1%
Other values (4739) 4739
99.8%
2024-11-04T23:00:33.285655image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 31676
 
8.4%
- 29627
 
7.9%
s 24123
 
6.4%
/ 23745
 
6.3%
t 21659
 
5.8%
o 20121
 
5.4%
w 16276
 
4.3%
a 14981
 
4.0%
i 14928
 
4.0%
p 14194
 
3.8%
Other values (30) 164293
43.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 375623
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 31676
 
8.4%
- 29627
 
7.9%
s 24123
 
6.4%
/ 23745
 
6.3%
t 21659
 
5.8%
o 20121
 
5.4%
w 16276
 
4.3%
a 14981
 
4.0%
i 14928
 
4.0%
p 14194
 
3.8%
Other values (30) 164293
43.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 375623
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 31676
 
8.4%
- 29627
 
7.9%
s 24123
 
6.4%
/ 23745
 
6.3%
t 21659
 
5.8%
o 20121
 
5.4%
w 16276
 
4.3%
a 14981
 
4.0%
i 14928
 
4.0%
p 14194
 
3.8%
Other values (30) 164293
43.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 375623
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 31676
 
8.4%
- 29627
 
7.9%
s 24123
 
6.4%
/ 23745
 
6.3%
t 21659
 
5.8%
o 20121
 
5.4%
w 16276
 
4.3%
a 14981
 
4.0%
i 14928
 
4.0%
p 14194
 
3.8%
Other values (30) 164293
43.7%

name
Text

Distinct2354
Distinct (%)49.6%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:33.688444image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length129
Median length121
Mean length15.000421
Min length2

Characters and Unicode

Total characters71237
Distinct characters436
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2165 ?
Unique (%)45.6%

Sample

1st rowСерия 1
2nd rowСерия 2
3rd rowСерия 3
4th rowСерия 4
5th rowСерия 5
ValueCountFrequency (%)
episode 2451
 
18.3%
the 382
 
2.8%
1 190
 
1.4%
2 189
 
1.4%
серия 180
 
1.3%
3 156
 
1.2%
4 147
 
1.1%
141
 
1.1%
5 134
 
1.0%
6 128
 
1.0%
Other values (4332) 9330
69.5%
2024-11-04T23:00:34.300598image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8687
 
12.2%
e 5846
 
8.2%
o 4564
 
6.4%
i 4404
 
6.2%
s 4090
 
5.7%
d 3391
 
4.8%
p 2925
 
4.1%
E 2776
 
3.9%
a 2567
 
3.6%
n 2129
 
3.0%
Other values (426) 29858
41.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 71237
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8687
 
12.2%
e 5846
 
8.2%
o 4564
 
6.4%
i 4404
 
6.2%
s 4090
 
5.7%
d 3391
 
4.8%
p 2925
 
4.1%
E 2776
 
3.9%
a 2567
 
3.6%
n 2129
 
3.0%
Other values (426) 29858
41.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 71237
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8687
 
12.2%
e 5846
 
8.2%
o 4564
 
6.4%
i 4404
 
6.2%
s 4090
 
5.7%
d 3391
 
4.8%
p 2925
 
4.1%
E 2776
 
3.9%
a 2567
 
3.6%
n 2129
 
3.0%
Other values (426) 29858
41.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 71237
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8687
 
12.2%
e 5846
 
8.2%
o 4564
 
6.4%
i 4404
 
6.2%
s 4090
 
5.7%
d 3391
 
4.8%
p 2925
 
4.1%
E 2776
 
3.9%
a 2567
 
3.6%
n 2129
 
3.0%
Other values (426) 29858
41.9%

season
Real number (ℝ)

High correlation 

Distinct34
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean300.31122
Minimum1
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:34.487255image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q36
95-th percentile2024
Maximum2024
Range2023
Interquartile range (IQR)5

Descriptive statistics

Standard deviation715.58742
Coefficient of variation (CV)2.3828194
Kurtosis1.9788381
Mean300.31122
Median Absolute Deviation (MAD)0
Skewness1.9943771
Sum1426178
Variance512065.36
MonotonicityNot monotonic
2024-11-04T23:00:34.656318image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 2508
52.8%
2024 694
 
14.6%
2 547
 
11.5%
3 259
 
5.5%
4 112
 
2.4%
5 108
 
2.3%
6 73
 
1.5%
8 65
 
1.4%
25 36
 
0.8%
11 33
 
0.7%
Other values (24) 314
 
6.6%
ValueCountFrequency (%)
1 2508
52.8%
2 547
 
11.5%
3 259
 
5.5%
4 112
 
2.4%
5 108
 
2.3%
6 73
 
1.5%
7 25
 
0.5%
8 65
 
1.4%
9 27
 
0.6%
10 30
 
0.6%
ValueCountFrequency (%)
2024 694
14.6%
2023 4
 
0.1%
54 4
 
0.1%
50 3
 
0.1%
41 8
 
0.2%
39 19
 
0.4%
34 4
 
0.1%
31 5
 
0.1%
30 20
 
0.4%
27 6
 
0.1%

number
Real number (ℝ)

High correlation 

Distinct183
Distinct (%)3.9%
Missing29
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean19.094915
Minimum1
Maximum959
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:34.951322image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8
Q318
95-th percentile67
Maximum959
Range958
Interquartile range (IQR)14

Descriptive statistics

Standard deviation47.861174
Coefficient of variation (CV)2.5064879
Kurtosis174.61148
Mean19.094915
Median Absolute Deviation (MAD)6
Skewness11.043834
Sum90128
Variance2290.692
MonotonicityNot monotonic
2024-11-04T23:00:35.131351image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 396
 
8.3%
2 371
 
7.8%
3 351
 
7.4%
4 312
 
6.6%
5 274
 
5.8%
6 255
 
5.4%
7 214
 
4.5%
8 203
 
4.3%
9 157
 
3.3%
10 146
 
3.1%
Other values (173) 2041
43.0%
ValueCountFrequency (%)
1 396
8.3%
2 371
7.8%
3 351
7.4%
4 312
6.6%
5 274
5.8%
6 255
5.4%
7 214
4.5%
8 203
4.3%
9 157
 
3.3%
10 146
 
3.1%
ValueCountFrequency (%)
959 1
< 0.1%
958 1
< 0.1%
957 1
< 0.1%
956 1
< 0.1%
955 1
< 0.1%
407 1
< 0.1%
406 1
< 0.1%
405 1
< 0.1%
404 1
< 0.1%
403 1
< 0.1%

type
Categorical

High correlation  Imbalance 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
regular
4720 
significant_special
 
18
insignificant_special
 
11

Length

Max length21
Median length7
Mean length7.0779111
Min length7

Characters and Unicode

Total characters33613
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular 4720
99.4%
significant_special 18
 
0.4%
insignificant_special 11
 
0.2%

Length

2024-11-04T23:00:35.289927image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-04T23:00:35.406616image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
regular 4720
99.4%
significant_special 18
 
0.4%
insignificant_special 11
 
0.2%

Most occurring characters

ValueCountFrequency (%)
r 9440
28.1%
a 4778
14.2%
e 4749
14.1%
g 4749
14.1%
l 4749
14.1%
u 4720
14.0%
i 127
 
0.4%
n 69
 
0.2%
s 58
 
0.2%
c 58
 
0.2%
Other values (4) 116
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 33613
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 9440
28.1%
a 4778
14.2%
e 4749
14.1%
g 4749
14.1%
l 4749
14.1%
u 4720
14.0%
i 127
 
0.4%
n 69
 
0.2%
s 58
 
0.2%
c 58
 
0.2%
Other values (4) 116
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 33613
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 9440
28.1%
a 4778
14.2%
e 4749
14.1%
g 4749
14.1%
l 4749
14.1%
u 4720
14.0%
i 127
 
0.4%
n 69
 
0.2%
s 58
 
0.2%
c 58
 
0.2%
Other values (4) 116
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 33613
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 9440
28.1%
a 4778
14.2%
e 4749
14.1%
g 4749
14.1%
l 4749
14.1%
u 4720
14.0%
i 127
 
0.4%
n 69
 
0.2%
s 58
 
0.2%
c 58
 
0.2%
Other values (4) 116
 
0.3%
Distinct31
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
Minimum2024-01-01 00:00:00
Maximum2024-01-31 00:00:00
2024-11-04T23:00:35.537232image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:35.715091image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

airtime
Date

Missing 

Distinct65
Distinct (%)2.8%
Missing2444
Missing (%)51.5%
Memory size37.2 KiB
Minimum2024-11-04 00:00:00
Maximum2024-11-04 23:35:00
2024-11-04T23:00:35.888593image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:36.058395image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct855
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
Minimum2024-01-01 00:00:00+00:00
Maximum2024-02-01 04:35:00+00:00
2024-11-04T23:00:36.241709image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:36.434194image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

runtime
Real number (ℝ)

High correlation 

Distinct109
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.344426
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:36.612716image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q121
median43
Q347
95-th percentile120
Maximum300
Range299
Interquartile range (IQR)26

Descriptive statistics

Standard deviation41.55122
Coefficient of variation (CV)0.9370111
Kurtosis13.278107
Mean44.344426
Median Absolute Deviation (MAD)15
Skewness3.2284429
Sum210591.68
Variance1726.5038
MonotonicityNot monotonic
2024-11-04T23:00:36.802783image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45 578
 
12.2%
44.34442634 452
 
9.5%
15 314
 
6.6%
60 304
 
6.4%
30 205
 
4.3%
10 181
 
3.8%
120 142
 
3.0%
40 116
 
2.4%
12 116
 
2.4%
3 116
 
2.4%
Other values (99) 2225
46.9%
ValueCountFrequency (%)
1 7
 
0.1%
2 43
 
0.9%
3 116
2.4%
4 4
 
0.1%
5 41
 
0.9%
6 17
 
0.4%
7 39
 
0.8%
8 51
 
1.1%
9 17
 
0.4%
10 181
3.8%
ValueCountFrequency (%)
300 23
 
0.5%
240 71
1.5%
210 3
 
0.1%
205 1
 
< 0.1%
180 35
0.7%
173 1
 
< 0.1%
159 27
 
0.6%
150 3
 
0.1%
149 1
 
< 0.1%
142 2
 
< 0.1%

rating
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size37.2 KiB
Distinct1460
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:37.245748image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length2299
Median length20
Mean length78.260476
Min length20

Characters and Unicode

Total characters371659
Distinct characters163
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1453 ?
Unique (%)30.6%

Sample

1st rowNo summary available
2nd rowNo summary available
3rd rowNo summary available
4th rowNo summary available
5th rowNo summary available
ValueCountFrequency (%)
no 3309
 
5.5%
available 3285
 
5.5%
summary 3284
 
5.5%
the 2665
 
4.4%
and 1704
 
2.8%
a 1684
 
2.8%
to 1657
 
2.8%
of 967
 
1.6%
in 800
 
1.3%
with 552
 
0.9%
Other values (11259) 40226
66.9%
2024-11-04T23:00:37.879005image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55231
14.9%
a 32971
 
8.9%
e 31274
 
8.4%
i 20233
 
5.4%
o 19660
 
5.3%
s 19462
 
5.2%
t 19357
 
5.2%
r 17834
 
4.8%
n 16925
 
4.6%
l 15772
 
4.2%
Other values (153) 122940
33.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 371659
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
55231
14.9%
a 32971
 
8.9%
e 31274
 
8.4%
i 20233
 
5.4%
o 19660
 
5.3%
s 19462
 
5.2%
t 19357
 
5.2%
r 17834
 
4.8%
n 16925
 
4.6%
l 15772
 
4.2%
Other values (153) 122940
33.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 371659
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
55231
14.9%
a 32971
 
8.9%
e 31274
 
8.4%
i 20233
 
5.4%
o 19660
 
5.3%
s 19462
 
5.2%
t 19357
 
5.2%
r 17834
 
4.8%
n 16925
 
4.6%
l 15772
 
4.2%
Other values (153) 122940
33.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 371659
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
55231
14.9%
a 32971
 
8.9%
e 31274
 
8.4%
i 20233
 
5.4%
o 19660
 
5.3%
s 19462
 
5.2%
t 19357
 
5.2%
r 17834
 
4.8%
n 16925
 
4.6%
l 15772
 
4.2%
Other values (153) 122940
33.1%

links_self
Text

Unique 

Distinct4749
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:38.137255image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters185211
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4749 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2730586
2nd rowhttps://api.tvmaze.com/episodes/2730587
3rd rowhttps://api.tvmaze.com/episodes/2730588
4th rowhttps://api.tvmaze.com/episodes/2730589
5th rowhttps://api.tvmaze.com/episodes/2730590
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/2692646 1
 
< 0.1%
https://api.tvmaze.com/episodes/2751926 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730586 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730587 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730588 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730589 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730590 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730591 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730592 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730593 1
 
< 0.1%
Other values (4739) 4739
99.8%
2024-11-04T23:00:38.527244image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 18996
 
10.3%
t 14247
 
7.7%
s 14247
 
7.7%
p 14247
 
7.7%
e 14247
 
7.7%
. 9498
 
5.1%
i 9498
 
5.1%
o 9498
 
5.1%
m 9498
 
5.1%
a 9498
 
5.1%
Other values (16) 61737
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 185211
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 18996
 
10.3%
t 14247
 
7.7%
s 14247
 
7.7%
p 14247
 
7.7%
e 14247
 
7.7%
. 9498
 
5.1%
i 9498
 
5.1%
o 9498
 
5.1%
m 9498
 
5.1%
a 9498
 
5.1%
Other values (16) 61737
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 185211
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 18996
 
10.3%
t 14247
 
7.7%
s 14247
 
7.7%
p 14247
 
7.7%
e 14247
 
7.7%
. 9498
 
5.1%
i 9498
 
5.1%
o 9498
 
5.1%
m 9498
 
5.1%
a 9498
 
5.1%
Other values (16) 61737
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 185211
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 18996
 
10.3%
t 14247
 
7.7%
s 14247
 
7.7%
p 14247
 
7.7%
e 14247
 
7.7%
. 9498
 
5.1%
i 9498
 
5.1%
o 9498
 
5.1%
m 9498
 
5.1%
a 9498
 
5.1%
Other values (16) 61737
33.3%
Distinct683
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:38.805233image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length34
Median length34
Mean length33.935355
Min length32

Characters and Unicode

Total characters161159
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)1.8%

Sample

1st rowhttps://api.tvmaze.com/shows/51908
2nd rowhttps://api.tvmaze.com/shows/51908
3rd rowhttps://api.tvmaze.com/shows/51908
4th rowhttps://api.tvmaze.com/shows/51908
5th rowhttps://api.tvmaze.com/shows/51908
ValueCountFrequency (%)
https://api.tvmaze.com/shows/78854 100
 
2.1%
https://api.tvmaze.com/shows/73952 38
 
0.8%
https://api.tvmaze.com/shows/73773 36
 
0.8%
https://api.tvmaze.com/shows/73703 36
 
0.8%
https://api.tvmaze.com/shows/72654 36
 
0.8%
https://api.tvmaze.com/shows/74045 34
 
0.7%
https://api.tvmaze.com/shows/42056 33
 
0.7%
https://api.tvmaze.com/shows/69806 32
 
0.7%
https://api.tvmaze.com/shows/73931 30
 
0.6%
https://api.tvmaze.com/shows/73862 28
 
0.6%
Other values (673) 4346
91.5%
2024-11-04T23:00:39.252799image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 18996
 
11.8%
t 14247
 
8.8%
s 14247
 
8.8%
h 9498
 
5.9%
p 9498
 
5.9%
a 9498
 
5.9%
. 9498
 
5.9%
m 9498
 
5.9%
o 9498
 
5.9%
: 4749
 
2.9%
Other values (16) 51932
32.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 161159
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 18996
 
11.8%
t 14247
 
8.8%
s 14247
 
8.8%
h 9498
 
5.9%
p 9498
 
5.9%
a 9498
 
5.9%
. 9498
 
5.9%
m 9498
 
5.9%
o 9498
 
5.9%
: 4749
 
2.9%
Other values (16) 51932
32.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 161159
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 18996
 
11.8%
t 14247
 
8.8%
s 14247
 
8.8%
h 9498
 
5.9%
p 9498
 
5.9%
a 9498
 
5.9%
. 9498
 
5.9%
m 9498
 
5.9%
o 9498
 
5.9%
: 4749
 
2.9%
Other values (16) 51932
32.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 161159
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 18996
 
11.8%
t 14247
 
8.8%
s 14247
 
8.8%
h 9498
 
5.9%
p 9498
 
5.9%
a 9498
 
5.9%
. 9498
 
5.9%
m 9498
 
5.9%
o 9498
 
5.9%
: 4749
 
2.9%
Other values (16) 51932
32.2%
Distinct681
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:39.576165image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length63
Median length41
Mean length17.492314
Min length2

Characters and Unicode

Total characters83071
Distinct characters167
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)1.8%

Sample

1st rowНежность
2nd rowНежность
3rd rowНежность
4th rowНежность
5th rowНежность
ValueCountFrequency (%)
the 777
 
5.2%
of 340
 
2.3%
my 226
 
1.5%
love 179
 
1.2%
news 171
 
1.1%
a 169
 
1.1%
and 160
 
1.1%
with 130
 
0.9%
you 122
 
0.8%
world 108
 
0.7%
Other values (1397) 12493
84.0%
2024-11-04T23:00:40.221035image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10126
 
12.2%
e 7443
 
9.0%
a 5035
 
6.1%
o 4573
 
5.5%
i 4307
 
5.2%
n 4238
 
5.1%
r 3885
 
4.7%
t 3378
 
4.1%
s 3157
 
3.8%
l 2473
 
3.0%
Other values (157) 34456
41.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 83071
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
10126
 
12.2%
e 7443
 
9.0%
a 5035
 
6.1%
o 4573
 
5.5%
i 4307
 
5.2%
n 4238
 
5.1%
r 3885
 
4.7%
t 3378
 
4.1%
s 3157
 
3.8%
l 2473
 
3.0%
Other values (157) 34456
41.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 83071
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
10126
 
12.2%
e 7443
 
9.0%
a 5035
 
6.1%
o 4573
 
5.5%
i 4307
 
5.2%
n 4238
 
5.1%
r 3885
 
4.7%
t 3378
 
4.1%
s 3157
 
3.8%
l 2473
 
3.0%
Other values (157) 34456
41.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 83071
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
10126
 
12.2%
e 7443
 
9.0%
a 5035
 
6.1%
o 4573
 
5.5%
i 4307
 
5.2%
n 4238
 
5.1%
r 3885
 
4.7%
t 3378
 
4.1%
s 3157
 
3.8%
l 2473
 
3.0%
Other values (157) 34456
41.5%

show_id
Real number (ℝ)

High correlation 

Distinct683
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63462.241
Minimum274
Maximum80603
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:40.391439image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum274
5-th percentile11502
Q159613
median72501
Q374045
95-th percentile77453
Maximum80603
Range80329
Interquartile range (IQR)14432

Descriptive statistics

Standard deviation18769.442
Coefficient of variation (CV)0.29575763
Kurtosis3.1901886
Mean63462.241
Median Absolute Deviation (MAD)3717
Skewness-1.9746208
Sum3.0138218 × 108
Variance3.5229195 × 108
MonotonicityNot monotonic
2024-11-04T23:00:40.585821image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
78854 100
 
2.1%
73952 38
 
0.8%
73773 36
 
0.8%
72654 36
 
0.8%
73703 36
 
0.8%
74045 34
 
0.7%
42056 33
 
0.7%
69806 32
 
0.7%
73931 30
 
0.6%
74100 28
 
0.6%
Other values (673) 4346
91.5%
ValueCountFrequency (%)
274 6
 
0.1%
703 4
 
0.1%
718 17
0.4%
729 4
 
0.1%
793 19
0.4%
802 5
 
0.1%
812 23
0.5%
875 3
 
0.1%
920 8
 
0.2%
938 6
 
0.1%
ValueCountFrequency (%)
80603 8
 
0.2%
80412 5
 
0.1%
80352 2
 
< 0.1%
80138 4
 
0.1%
80137 2
 
< 0.1%
79953 2
 
< 0.1%
79903 23
0.5%
79454 8
 
0.2%
79449 1
 
< 0.1%
78906 2
 
< 0.1%
Distinct683
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:40.875377image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length97
Median length73
Mean length52.210571
Min length35

Characters and Unicode

Total characters247948
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)1.8%

Sample

1st rowhttps://www.tvmaze.com/shows/51908/neznost
2nd rowhttps://www.tvmaze.com/shows/51908/neznost
3rd rowhttps://www.tvmaze.com/shows/51908/neznost
4th rowhttps://www.tvmaze.com/shows/51908/neznost
5th rowhttps://www.tvmaze.com/shows/51908/neznost
ValueCountFrequency (%)
https://www.tvmaze.com/shows/78854/my-beautiful-dumb-wife 100
 
2.1%
https://www.tvmaze.com/shows/73952/shanghai-picked-flowers 38
 
0.8%
https://www.tvmaze.com/shows/73773/my-boss 36
 
0.8%
https://www.tvmaze.com/shows/73703/just-between-us 36
 
0.8%
https://www.tvmaze.com/shows/72654/our-interpreter 36
 
0.8%
https://www.tvmaze.com/shows/74045/sword-and-fairy-4 34
 
0.7%
https://www.tvmaze.com/shows/42056/like-a-flowing-river 33
 
0.7%
https://www.tvmaze.com/shows/69806/scout-hero 32
 
0.7%
https://www.tvmaze.com/shows/73931/different-princess 30
 
0.6%
https://www.tvmaze.com/shows/73862/born-to-run 28
 
0.6%
Other values (673) 4346
91.5%
2024-11-04T23:00:41.359953image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 23745
 
9.6%
w 20495
 
8.3%
t 18990
 
7.7%
s 18967
 
7.6%
o 14793
 
6.0%
e 12871
 
5.2%
h 12456
 
5.0%
m 11647
 
4.7%
a 11057
 
4.5%
- 10082
 
4.1%
Other values (30) 92845
37.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 247948
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 23745
 
9.6%
w 20495
 
8.3%
t 18990
 
7.7%
s 18967
 
7.6%
o 14793
 
6.0%
e 12871
 
5.2%
h 12456
 
5.0%
m 11647
 
4.7%
a 11057
 
4.5%
- 10082
 
4.1%
Other values (30) 92845
37.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 247948
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 23745
 
9.6%
w 20495
 
8.3%
t 18990
 
7.7%
s 18967
 
7.6%
o 14793
 
6.0%
e 12871
 
5.2%
h 12456
 
5.0%
m 11647
 
4.7%
a 11057
 
4.5%
- 10082
 
4.1%
Other values (30) 92845
37.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 247948
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 23745
 
9.6%
w 20495
 
8.3%
t 18990
 
7.7%
s 18967
 
7.6%
o 14793
 
6.0%
e 12871
 
5.2%
h 12456
 
5.0%
m 11647
 
4.7%
a 11057
 
4.5%
- 10082
 
4.1%
Other values (30) 92845
37.4%
Distinct681
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:41.690331image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length63
Median length41
Mean length17.492314
Min length2

Characters and Unicode

Total characters83071
Distinct characters167
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)1.8%

Sample

1st rowНежность
2nd rowНежность
3rd rowНежность
4th rowНежность
5th rowНежность
ValueCountFrequency (%)
the 777
 
5.2%
of 340
 
2.3%
my 226
 
1.5%
love 179
 
1.2%
news 171
 
1.1%
a 169
 
1.1%
and 160
 
1.1%
with 130
 
0.9%
you 122
 
0.8%
world 108
 
0.7%
Other values (1397) 12493
84.0%
2024-11-04T23:00:42.201218image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10126
 
12.2%
e 7443
 
9.0%
a 5035
 
6.1%
o 4573
 
5.5%
i 4307
 
5.2%
n 4238
 
5.1%
r 3885
 
4.7%
t 3378
 
4.1%
s 3157
 
3.8%
l 2473
 
3.0%
Other values (157) 34456
41.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 83071
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
10126
 
12.2%
e 7443
 
9.0%
a 5035
 
6.1%
o 4573
 
5.5%
i 4307
 
5.2%
n 4238
 
5.1%
r 3885
 
4.7%
t 3378
 
4.1%
s 3157
 
3.8%
l 2473
 
3.0%
Other values (157) 34456
41.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 83071
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
10126
 
12.2%
e 7443
 
9.0%
a 5035
 
6.1%
o 4573
 
5.5%
i 4307
 
5.2%
n 4238
 
5.1%
r 3885
 
4.7%
t 3378
 
4.1%
s 3157
 
3.8%
l 2473
 
3.0%
Other values (157) 34456
41.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 83071
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
10126
 
12.2%
e 7443
 
9.0%
a 5035
 
6.1%
o 4573
 
5.5%
i 4307
 
5.2%
n 4238
 
5.1%
r 3885
 
4.7%
t 3378
 
4.1%
s 3157
 
3.8%
l 2473
 
3.0%
Other values (157) 34456
41.5%

show_type
Categorical

High correlation 

Distinct11
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
Scripted
2224 
Animation
643 
News
534 
Reality
499 
Documentary
324 
Other values (6)
525 

Length

Max length11
Median length10
Mean length7.8418614
Min length4

Characters and Unicode

Total characters37241
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowScripted
2nd rowScripted
3rd rowScripted
4th rowScripted
5th rowScripted

Common Values

ValueCountFrequency (%)
Scripted 2224
46.8%
Animation 643
 
13.5%
News 534
 
11.2%
Reality 499
 
10.5%
Documentary 324
 
6.8%
Talk Show 287
 
6.0%
Game Show 114
 
2.4%
Variety 56
 
1.2%
Sports 53
 
1.1%
Panel Show 14
 
0.3%

Length

2024-11-04T23:00:42.372096image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
scripted 2224
43.1%
animation 643
 
12.4%
news 534
 
10.3%
reality 499
 
9.7%
show 416
 
8.1%
documentary 324
 
6.3%
talk 287
 
5.6%
game 114
 
2.2%
variety 56
 
1.1%
sports 53
 
1.0%
Other values (2) 15
 
0.3%

Most occurring characters

ValueCountFrequency (%)
i 4065
10.9%
t 3799
 
10.2%
e 3765
 
10.1%
S 2693
 
7.2%
r 2658
 
7.1%
c 2548
 
6.8%
p 2277
 
6.1%
d 2225
 
6.0%
a 1938
 
5.2%
n 1624
 
4.4%
Other values (18) 9649
25.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 37241
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 4065
10.9%
t 3799
 
10.2%
e 3765
 
10.1%
S 2693
 
7.2%
r 2658
 
7.1%
c 2548
 
6.8%
p 2277
 
6.1%
d 2225
 
6.0%
a 1938
 
5.2%
n 1624
 
4.4%
Other values (18) 9649
25.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 37241
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 4065
10.9%
t 3799
 
10.2%
e 3765
 
10.1%
S 2693
 
7.2%
r 2658
 
7.1%
c 2548
 
6.8%
p 2277
 
6.1%
d 2225
 
6.0%
a 1938
 
5.2%
n 1624
 
4.4%
Other values (18) 9649
25.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 37241
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 4065
10.9%
t 3799
 
10.2%
e 3765
 
10.1%
S 2693
 
7.2%
r 2658
 
7.1%
c 2548
 
6.8%
p 2277
 
6.1%
d 2225
 
6.0%
a 1938
 
5.2%
n 1624
 
4.4%
Other values (18) 9649
25.9%

show_language
Categorical

High correlation 

Distinct33
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
english
1957 
chinese
1506 
russian
246 
norwegian
 
177
korean
 
106
Other values (28)
757 

Length

Max length10
Median length7
Mean length6.9964203
Min length4

Characters and Unicode

Total characters33226
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowrussian
2nd rowrussian
3rd rowrussian
4th rowrussian
5th rowrussian

Common Values

ValueCountFrequency (%)
english 1957
41.2%
chinese 1506
31.7%
russian 246
 
5.2%
norwegian 177
 
3.7%
korean 106
 
2.2%
spanish 86
 
1.8%
arabic 76
 
1.6%
swedish 73
 
1.5%
japanese 69
 
1.5%
hindi 66
 
1.4%
Other values (23) 387
 
8.1%

Length

2024-11-04T23:00:42.527754image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english 1957
41.2%
chinese 1506
31.7%
russian 246
 
5.2%
norwegian 177
 
3.7%
korean 106
 
2.2%
spanish 86
 
1.8%
arabic 76
 
1.6%
swedish 73
 
1.5%
japanese 69
 
1.5%
hindi 66
 
1.4%
Other values (23) 387
 
8.1%

Most occurring characters

ValueCountFrequency (%)
e 5578
16.8%
n 4667
14.0%
i 4593
13.8%
s 4504
13.6%
h 3933
11.8%
g 2207
 
6.6%
l 2037
 
6.1%
c 1650
 
5.0%
a 1250
 
3.8%
r 800
 
2.4%
Other values (14) 2007
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 33226
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 5578
16.8%
n 4667
14.0%
i 4593
13.8%
s 4504
13.6%
h 3933
11.8%
g 2207
 
6.6%
l 2037
 
6.1%
c 1650
 
5.0%
a 1250
 
3.8%
r 800
 
2.4%
Other values (14) 2007
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 33226
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 5578
16.8%
n 4667
14.0%
i 4593
13.8%
s 4504
13.6%
h 3933
11.8%
g 2207
 
6.6%
l 2037
 
6.1%
c 1650
 
5.0%
a 1250
 
3.8%
r 800
 
2.4%
Other values (14) 2007
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 33226
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 5578
16.8%
n 4667
14.0%
i 4593
13.8%
s 4504
13.6%
h 3933
11.8%
g 2207
 
6.6%
l 2037
 
6.1%
c 1650
 
5.0%
a 1250
 
3.8%
r 800
 
2.4%
Other values (14) 2007
 
6.0%

show_genres
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size37.2 KiB

show_status
Categorical

High correlation 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
running
2390 
ended
1710 
to be determined
649 

Length

Max length16
Median length7
Mean length7.5097915
Min length5

Characters and Unicode

Total characters35664
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowended
2nd rowended
3rd rowended
4th rowended
5th rowended

Common Values

ValueCountFrequency (%)
running 2390
50.3%
ended 1710
36.0%
to be determined 649
 
13.7%

Length

2024-11-04T23:00:42.676390image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-04T23:00:42.791157image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
running 2390
39.5%
ended 1710
28.3%
to 649
 
10.7%
be 649
 
10.7%
determined 649
 
10.7%

Most occurring characters

ValueCountFrequency (%)
n 9529
26.7%
e 6016
16.9%
d 4718
13.2%
r 3039
 
8.5%
i 3039
 
8.5%
u 2390
 
6.7%
g 2390
 
6.7%
t 1298
 
3.6%
1298
 
3.6%
o 649
 
1.8%
Other values (2) 1298
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 35664
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 9529
26.7%
e 6016
16.9%
d 4718
13.2%
r 3039
 
8.5%
i 3039
 
8.5%
u 2390
 
6.7%
g 2390
 
6.7%
t 1298
 
3.6%
1298
 
3.6%
o 649
 
1.8%
Other values (2) 1298
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 35664
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 9529
26.7%
e 6016
16.9%
d 4718
13.2%
r 3039
 
8.5%
i 3039
 
8.5%
u 2390
 
6.7%
g 2390
 
6.7%
t 1298
 
3.6%
1298
 
3.6%
o 649
 
1.8%
Other values (2) 1298
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 35664
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 9529
26.7%
e 6016
16.9%
d 4718
13.2%
r 3039
 
8.5%
i 3039
 
8.5%
u 2390
 
6.7%
g 2390
 
6.7%
t 1298
 
3.6%
1298
 
3.6%
o 649
 
1.8%
Other values (2) 1298
 
3.6%

show_averageRuntime
Real number (ℝ)

High correlation 

Distinct100
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.422878
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:42.939726image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q120
median43
Q350
95-th percentile120
Maximum300
Range299
Interquartile range (IQR)30

Descriptive statistics

Standard deviation41.506833
Coefficient of variation (CV)0.93435713
Kurtosis13.254459
Mean44.422878
Median Absolute Deviation (MAD)17
Skewness3.208881
Sum210964.25
Variance1722.8172
MonotonicityNot monotonic
2024-11-04T23:00:43.112490image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45 576
 
12.1%
60 334
 
7.0%
15 312
 
6.6%
44.42287773 308
 
6.5%
30 247
 
5.2%
10 220
 
4.6%
43 140
 
2.9%
120 136
 
2.9%
3 119
 
2.5%
25 108
 
2.3%
Other values (90) 2249
47.4%
ValueCountFrequency (%)
1 6
 
0.1%
2 42
 
0.9%
3 119
2.5%
4 3
 
0.1%
5 33
 
0.7%
6 9
 
0.2%
7 52
 
1.1%
8 43
 
0.9%
9 19
 
0.4%
10 220
4.6%
ValueCountFrequency (%)
300 23
 
0.5%
242 2
 
< 0.1%
240 69
1.5%
218 1
 
< 0.1%
194 1
 
< 0.1%
184 1
 
< 0.1%
180 30
0.6%
177 4
 
0.1%
164 3
 
0.1%
163 27
 
0.6%
Distinct456
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
Minimum1944-01-20 00:00:00
Maximum2024-02-09 00:00:00
2024-11-04T23:00:43.282434image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:43.468429image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

show_ended
Date

Missing 

Distinct76
Distinct (%)4.4%
Missing3039
Missing (%)64.0%
Memory size37.2 KiB
Minimum2024-01-01 00:00:00
Maximum2024-11-09 00:00:00
2024-11-04T23:00:43.699039image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:43.932047image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct608
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:44.196624image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length250
Median length106
Mean length47.798273
Min length7

Characters and Unicode

Total characters226994
Distinct characters96
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)1.5%

Sample

1st rowhttps://www.ivi.ru/watch/nezhnost
2nd rowhttps://www.ivi.ru/watch/nezhnost
3rd rowhttps://www.ivi.ru/watch/nezhnost
4th rowhttps://www.ivi.ru/watch/nezhnost
5th rowhttps://www.ivi.ru/watch/nezhnost
ValueCountFrequency (%)
unknown 450
 
9.5%
https://flameserial.ru/season/12949 100
 
2.1%
https://abcnews.go.com/live 92
 
1.9%
https://v.qq.com/x/cover/mzc002005kvupzf.html 38
 
0.8%
https://w.mgtv.com/b/610526/20301892.html?fpa=se&lastp=so_result 36
 
0.8%
https://w.mgtv.com/h/600824/20020678.html 36
 
0.8%
https://v.youku.com/v_nextstage/id_ebdb60223f3e44c7aadf.html?spm=a2h0c.8166622.phonesokuprogram_1.dtitle 36
 
0.8%
https://www.iq.com/album/sword-and-fairy-4-2024-13ndvpx4xm1?lang=en_us 34
 
0.7%
https://v.qq.com/x/cover/mzc00200syv5tor.html 33
 
0.7%
https://www.iq.com/album/scout-hero-2023-1oipynj6bzh?lang=en_us 32
 
0.7%
Other values (598) 3862
81.3%
2024-11-04T23:00:44.989006image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 18407
 
8.1%
t 15607
 
6.9%
o 10947
 
4.8%
s 10769
 
4.7%
. 10219
 
4.5%
e 9915
 
4.4%
w 9291
 
4.1%
h 8548
 
3.8%
m 8455
 
3.7%
c 7911
 
3.5%
Other values (86) 116925
51.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 226994
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 18407
 
8.1%
t 15607
 
6.9%
o 10947
 
4.8%
s 10769
 
4.7%
. 10219
 
4.5%
e 9915
 
4.4%
w 9291
 
4.1%
h 8548
 
3.8%
m 8455
 
3.7%
c 7911
 
3.5%
Other values (86) 116925
51.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 226994
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 18407
 
8.1%
t 15607
 
6.9%
o 10947
 
4.8%
s 10769
 
4.7%
. 10219
 
4.5%
e 9915
 
4.4%
w 9291
 
4.1%
h 8548
 
3.8%
m 8455
 
3.7%
c 7911
 
3.5%
Other values (86) 116925
51.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 226994
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 18407
 
8.1%
t 15607
 
6.9%
o 10947
 
4.8%
s 10769
 
4.7%
. 10219
 
4.5%
e 9915
 
4.4%
w 9291
 
4.1%
h 8548
 
3.8%
m 8455
 
3.7%
c 7911
 
3.5%
Other values (86) 116925
51.5%

show_rating
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size37.2 KiB

show_weight
Real number (ℝ)

High correlation  Zeros 

Distinct100
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.31354
Minimum0
Maximum100
Zeros146
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:45.170878image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q16
median23
Q350
95-th percentile94
Maximum100
Range100
Interquartile range (IQR)44

Descriptive statistics

Standard deviation29.863252
Coefficient of variation (CV)0.9241715
Kurtosis-0.54050165
Mean32.31354
Median Absolute Deviation (MAD)17
Skewness0.83905971
Sum153457
Variance891.81385
MonotonicityNot monotonic
2024-11-04T23:00:45.356192image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 701
 
14.8%
8 194
 
4.1%
3 172
 
3.6%
4 168
 
3.5%
12 164
 
3.5%
0 146
 
3.1%
9 128
 
2.7%
26 107
 
2.3%
18 98
 
2.1%
44 95
 
2.0%
Other values (90) 2776
58.5%
ValueCountFrequency (%)
0 146
 
3.1%
1 85
 
1.8%
2 60
 
1.3%
3 172
 
3.6%
4 168
 
3.5%
5 25
 
0.5%
6 701
14.8%
7 49
 
1.0%
8 194
 
4.1%
9 128
 
2.7%
ValueCountFrequency (%)
100 3
 
0.1%
99 36
0.8%
98 31
 
0.7%
97 26
 
0.5%
96 85
1.8%
95 26
 
0.5%
94 72
1.5%
93 6
 
0.1%
92 36
0.8%
91 30
 
0.6%

show_network
Unsupported

Missing  Rejected  Unsupported 

Missing4233
Missing (%)89.1%
Memory size37.2 KiB

show_summary
Text

Missing 

Distinct592
Distinct (%)14.9%
Missing779
Missing (%)16.4%
Memory size37.2 KiB
2024-11-04T23:00:45.860399image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1931
Median length637
Mean length382.77053
Min length50

Characters and Unicode

Total characters1519599
Distinct characters300
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)1.8%

Sample

1st row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
2nd row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
3rd row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
4th row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
5th row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
ValueCountFrequency (%)
the 15094
 
6.0%
and 9043
 
3.6%
to 7127
 
2.8%
of 7074
 
2.8%
a 6981
 
2.8%
in 4522
 
1.8%
is 2729
 
1.1%
with 2633
 
1.1%
her 2567
 
1.0%
his 2301
 
0.9%
Other values (8219) 190483
76.0%
2024-11-04T23:00:46.514969image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
246225
16.2%
e 145178
 
9.6%
t 95762
 
6.3%
a 95720
 
6.3%
n 89038
 
5.9%
i 88019
 
5.8%
o 84285
 
5.5%
s 76575
 
5.0%
r 72033
 
4.7%
h 64382
 
4.2%
Other values (290) 462382
30.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1519599
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
246225
16.2%
e 145178
 
9.6%
t 95762
 
6.3%
a 95720
 
6.3%
n 89038
 
5.9%
i 88019
 
5.8%
o 84285
 
5.5%
s 76575
 
5.0%
r 72033
 
4.7%
h 64382
 
4.2%
Other values (290) 462382
30.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1519599
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
246225
16.2%
e 145178
 
9.6%
t 95762
 
6.3%
a 95720
 
6.3%
n 89038
 
5.9%
i 88019
 
5.8%
o 84285
 
5.5%
s 76575
 
5.0%
r 72033
 
4.7%
h 64382
 
4.2%
Other values (290) 462382
30.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1519599
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
246225
16.2%
e 145178
 
9.6%
t 95762
 
6.3%
a 95720
 
6.3%
n 89038
 
5.9%
i 88019
 
5.8%
o 84285
 
5.5%
s 76575
 
5.0%
r 72033
 
4.7%
h 64382
 
4.2%
Other values (290) 462382
30.4%

show_updated
Real number (ℝ)

Distinct683
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7159103 × 109
Minimum1.6983432 × 109
Maximum1.730773 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.2 KiB
2024-11-04T23:00:46.737665image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.6983432 × 109
5-th percentile1.7048212 × 109
Q11.7066994 × 109
median1.7141713 × 109
Q31.7255617 × 109
95-th percentile1.730683 × 109
Maximum1.730773 × 109
Range32429839
Interquartile range (IQR)18862333

Descriptive statistics

Standard deviation9439582.3
Coefficient of variation (CV)0.0055012097
Kurtosis-1.4288165
Mean1.7159103 × 109
Median Absolute Deviation (MAD)8084654
Skewness0.30727005
Sum8.148858 × 1012
Variance8.9105714 × 1013
MonotonicityNot monotonic
2024-11-04T23:00:46.931637image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1723133542 100
 
2.1%
1707133992 38
 
0.8%
1706282249 36
 
0.8%
1706192291 36
 
0.8%
1705897985 36
 
0.8%
1706797142 34
 
0.7%
1711774278 33
 
0.7%
1706339205 32
 
0.7%
1706957455 30
 
0.6%
1706797129 28
 
0.6%
Other values (673) 4346
91.5%
ValueCountFrequency (%)
1698343176 4
0.1%
1699173762 4
0.1%
1699196321 3
0.1%
1700067953 1
 
< 0.1%
1701776723 7
0.1%
1703096478 4
0.1%
1703320852 7
0.1%
1703404987 3
0.1%
1703852377 4
0.1%
1703934794 4
0.1%
ValueCountFrequency (%)
1730773015 3
 
0.1%
1730768429 3
 
0.1%
1730767329 6
 
0.1%
1730766831 19
0.4%
1730766602 19
0.4%
1730765901 8
0.2%
1730764951 4
 
0.1%
1730763954 8
0.2%
1730763661 3
 
0.1%
1730763104 6
 
0.1%

show_links
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size37.2 KiB
Distinct31
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size37.2 KiB
Minimum2024-01-01 00:00:00
Maximum2024-01-31 00:00:00
2024-11-04T23:00:47.101310image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:47.301614image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

Interactions

2024-11-04T23:00:29.415311image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:19.588767image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:20.863143image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:22.173939image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:23.402641image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:24.931926image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:26.552300image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:28.057575image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:29.547393image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:19.756713image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:21.049762image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:22.303204image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:23.607417image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:25.123912image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:26.829392image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:28.310106image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:29.699687image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:19.915160image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:21.201024image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:22.476179image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:23.890908image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:25.302701image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:26.962934image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:28.499451image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:29.837344image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:20.072600image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:21.387752image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:22.641051image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:24.135874image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:25.535813image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:27.109844image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:28.635981image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:29.970129image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:20.227187image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:21.550297image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:22.804748image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:24.310406image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:25.689741image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:27.349115image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:28.760680image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:30.101705image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:20.401969image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:21.713930image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:22.953683image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:24.465025image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:25.964318image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:27.508385image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:28.926238image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:30.377946image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:20.538598image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:21.868125image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:23.142717image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:24.598337image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:26.182899image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:27.640637image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:29.065857image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:30.544597image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:20.693296image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:22.010098image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:23.271208image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:24.768351image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:26.324247image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:27.838156image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-04T23:00:29.197383image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-11-04T23:00:47.428791image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
idnumberruntimeseasonshow_averageRuntimeshow_idshow_languageshow_statusshow_typeshow_updatedshow_weighttype
id1.0000.0600.0140.2260.0160.4510.2260.1980.3990.293-0.3390.218
number0.0601.000-0.147-0.097-0.1680.0690.1090.0920.1010.013-0.0941.000
runtime0.014-0.1471.0000.3130.9410.0080.2340.1970.2770.0780.0870.078
season0.226-0.0970.3131.0000.357-0.3500.4350.4110.8290.4890.2590.000
show_averageRuntime0.016-0.1680.9410.3571.000-0.0190.2230.2000.2710.1180.1070.000
show_id0.4510.0690.008-0.350-0.0191.0000.2640.2920.219-0.152-0.6770.056
show_language0.2260.1090.2340.4350.2230.2641.0000.5510.3030.3050.2610.159
show_status0.1980.0920.1970.4110.2000.2920.5511.0000.5320.3950.3090.024
show_type0.3990.1010.2770.8290.2710.2190.3030.5321.0000.2130.1850.083
show_updated0.2930.0130.0780.4890.118-0.1520.3050.3950.2131.0000.3240.033
show_weight-0.339-0.0940.0870.2590.107-0.6770.2610.3090.1850.3241.0000.052
type0.2181.0000.0780.0000.0000.0560.1590.0240.0830.0330.0521.000

Missing values

2024-11-04T23:00:30.890671image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-11-04T23:00:31.631577image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-11-04T23:00:31.934294image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

idurlnameseasonnumbertypeairdateairtimeairstampruntimeratingsummarylinks_selflinks_show_hreflinks_show_nameshow_idshow_urlshow_nameshow_typeshow_languageshow_genresshow_statusshow_averageRuntimeshow_premieredshow_endedshow_officialSiteshow_ratingshow_weightshow_networkshow_summaryshow_updatedshow_linksextraction_date
02730586https://www.tvmaze.com/episodes/2730586/neznost-2x01-seria-1Серия 121.0regular2024-01-012024-01-01T00:00:00+00:0023.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730586https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
12730587https://www.tvmaze.com/episodes/2730587/neznost-2x02-seria-2Серия 222.0regular2024-01-012024-01-01T00:00:00+00:0020.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730587https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
22730588https://www.tvmaze.com/episodes/2730588/neznost-2x03-seria-3Серия 323.0regular2024-01-012024-01-01T00:00:00+00:0019.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730588https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
32730589https://www.tvmaze.com/episodes/2730589/neznost-2x04-seria-4Серия 424.0regular2024-01-012024-01-01T00:00:00+00:0021.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730589https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
42730590https://www.tvmaze.com/episodes/2730590/neznost-2x05-seria-5Серия 525.0regular2024-01-012024-01-01T00:00:00+00:0020.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730590https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
52730591https://www.tvmaze.com/episodes/2730591/neznost-2x06-seria-6Серия 626.0regular2024-01-012024-01-01T00:00:00+00:0020.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730591https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
62730592https://www.tvmaze.com/episodes/2730592/neznost-2x07-seria-7Серия 727.0regular2024-01-012024-01-01T00:00:00+00:0020.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730592https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
72730593https://www.tvmaze.com/episodes/2730593/neznost-2x08-seria-8Серия 828.0regular2024-01-012024-01-01T00:00:00+00:0019.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730593https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
82730594https://www.tvmaze.com/episodes/2730594/neznost-2x09-seria-9Серия 929.0regular2024-01-012024-01-01T00:00:00+00:0018.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730594https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
92730595https://www.tvmaze.com/episodes/2730595/neznost-2x10-seria-10Серия 10210.0regular2024-01-012024-01-01T00:00:00+00:0019.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730595https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
idurlnameseasonnumbertypeairdateairtimeairstampruntimeratingsummarylinks_selflinks_show_hreflinks_show_nameshow_idshow_urlshow_nameshow_typeshow_languageshow_genresshow_statusshow_averageRuntimeshow_premieredshow_endedshow_officialSiteshow_ratingshow_weightshow_networkshow_summaryshow_updatedshow_linksextraction_date
47392920526https://www.tvmaze.com/episodes/2920526/dromkakar-utomlands-1x04-avsnitt-4Avsnitt 414.0regular2024-01-3100:002024-01-31T23:00:00+00:0045.000000{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2920526https://api.tvmaze.com/shows/73778Drömkåkar utomlands73778https://www.tvmaze.com/shows/73778/dromkakar-utomlandsDrömkåkar utomlandsRealityswedish[]to be determined45.0000002024-01-10Nonehttps://www.tv4play.se/program/9e5573b08abbda332d28/dromkakar-utomlands{'average': None}3None<p>For two years, we get to follow Swedes who build and renovate the houses they dreamed of, abroad. But the journey to the dream home is not always straight.</p>1718874160{'self': {'href': 'https://api.tvmaze.com/shows/73778'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2920530', 'name': 'Avsnitt 8'}}2024-01-31
47402761042https://www.tvmaze.com/episodes/2761042/dimension-20-21x04-under-pressureUnder Pressure214.0regular2024-01-3119:002024-02-01T00:00:00+00:0044.344426{'average': None}<p>The Bad Kids realize how much work they'll be balancing this year. Adaine gets a job.</p>https://api.tvmaze.com/episodes/2761042https://api.tvmaze.com/shows/56531Dimension 2056531https://www.tvmaze.com/shows/56531/dimension-20Dimension 20Game Showenglish[Comedy, Adventure, Fantasy]running107.0000002018-09-12Nonehttps://www.dropout.tv/dimension-20{'average': None}86None<p>Heed the call of adventure and enter <b>Dimension 20</b> where Game Master Brennan Lee Mulligan, joined by comedians and pro gamers, blends comedy with tabletop RPGs.</p>1730579750{'self': {'href': 'https://api.tvmaze.com/shows/56531'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/3041299', 'name': 'Code Crimson'}}2024-01-31
47412794533https://www.tvmaze.com/episodes/2794533/the-daily-report-with-john-dickerson-2024-01-31-episode-18Episode 18202418.0regular2024-01-3119:002024-02-01T00:00:00+00:0060.000000{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2794533https://api.tvmaze.com/shows/75261The Daily Report with John Dickerson75261https://www.tvmaze.com/shows/75261/the-daily-report-with-john-dickersonThe Daily Report with John DickersonNewsenglish[]running60.0000002022-09-06Nonehttps://www.cbsnews.com/prime-time-with-john-dickerson/{'average': None}38None<p>John Dickerson provides in-depth reporting on news stories and interviews newsmakers.</p>1722688947{'self': {'href': 'https://api.tvmaze.com/shows/75261'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2966145', 'name': 'Episode 140'}}2024-01-31
47422833048https://www.tvmaze.com/episodes/2833048/abc-prime-with-linsey-davis-2024-01-31-episode-23Episode 23202423.0regular2024-01-3119:002024-02-01T00:00:00+00:0090.000000{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2833048https://api.tvmaze.com/shows/76215ABC Prime with Linsey Davis76215https://www.tvmaze.com/shows/76215/abc-prime-with-linsey-davisABC Prime with Linsey DavisNewsenglish[]running90.0000002020-02-17Nonehttps://abcnews.go.com/Live{'average': None}38None<p>Providing prime-time context and analysis of the day's top stories, as well as in-depth reporting and storytelling from around the country and the globe.</p>1728235929{'self': {'href': 'https://api.tvmaze.com/shows/76215'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/3013782', 'name': 'Episode 195'}}2024-01-31
47432750457https://www.tvmaze.com/episodes/2750457/camilla-hamids-bakresa-marocko-1x02-avsnitt-2Avsnitt 212.0regular2024-01-3102:002024-02-01T01:00:00+00:0044.344426{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2750457https://api.tvmaze.com/shows/73963Camilla Hamids bakresa: Marocko73963https://www.tvmaze.com/shows/73963/camilla-hamids-bakresa-marockoCamilla Hamids bakresa: MarockoRealityswedish[]running44.4228782024-01-24Nonehttps://www.svtplay.se/camilla-hamids-bakresa-marocko{'average': None}3None<p>Come along to Camilla's Moroccan family where she gets to learn about the Moroccan baking culture together to understand more about where she belongs. Camilla has always felt too Swedish in Morocco and too Moroccan in Sweden and never really felt 100% at home anywhere. With this program, she hopes not only to offer new exciting baking pleasure, but also understanding and recognition.</p>1706117901{'self': {'href': 'https://api.tvmaze.com/shows/73963'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2750460', 'name': 'Avsnitt 5'}}2024-01-31
47442941639https://www.tvmaze.com/episodes/2941639/trafficked-with-mariana-van-zeller-4x03-body-partsBody Parts43.0regular2024-01-3121:002024-02-01T02:00:00+00:0060.000000{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2941639https://api.tvmaze.com/shows/49496Trafficked with Mariana van Zeller49496https://www.tvmaze.com/shows/49496/trafficked-with-mariana-van-zellerTrafficked with Mariana van ZellerDocumentaryenglish[Crime]to be determined62.0000002020-12-02Nonehttps://www.nationalgeographic.com/tv/shows/trafficked-with-mariana-van-zeller{'average': 7.8}89{'id': 42, 'name': 'National Geographic', 'country': {'name': 'United States', 'code': 'US', 'timezone': 'America/New_York'}, 'officialSite': 'https://www.nationalgeographic.com/tv/'}<p>Armed with National Geographic's trademark inside access, <b>Trafficked with Mariana van Zeller</b> takes viewers on a journey inside the most dangerous black markets on the planet. Each investigation in the eight-part series embeds with Peabody and duPont Award-winning journalist Mariana van Zeller as she explores the complex and often violent inner workings of a smuggling network. While she dives deeper and deeper into these underworlds, Mariana reveals - with characteristic boldness and empathy - that the people operating these trafficking rings are often a lot more like us than we realize.</p>1720942651{'self': {'href': 'https://api.tvmaze.com/shows/49496'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2941650', 'name': 'Caught in an African Coup'}}2024-01-31
47452732350https://www.tvmaze.com/episodes/2732350/alle-elsker-david-5x15-viva-barcelona¡Viva Barcelona!515.0regular2024-01-3103:002024-02-01T02:00:00+00:0021.000000{'average': None}<p>The gang is in Barcelona and going to see Ingrid play a match. Andrea confronts her father about his future plans with Louise.</p>https://api.tvmaze.com/episodes/2732350https://api.tvmaze.com/shows/54476Alle Elsker David54476https://www.tvmaze.com/shows/54476/alle-elsker-davidAlle Elsker DavidRealitynorwegian[]to be determined22.0000002021-03-08Nonehttps://play.tv2.no/programmer/underholdning/alle-elsker-david{'average': None}20None<p>We follow manager David Eriksen and his charming but untraditional family. In David's new company, the pace is high and the drop is great.</p>1714772507{'self': {'href': 'https://api.tvmaze.com/shows/54476'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2732353', 'name': 'Sykemelding og flyttemelding'}}2024-01-31
47462765084https://www.tvmaze.com/episodes/2765084/disasterinas-my-drag-is-valid-1x15-luka-ghostLuka Ghost115.0regular2024-01-3100:002024-02-01T04:00:00+00:0044.344426{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2765084https://api.tvmaze.com/shows/73167Disasterina's My Drag Is Valid73167https://www.tvmaze.com/shows/73167/disasterinas-my-drag-is-validDisasterina's My Drag Is ValidTalk Showenglish[]running24.0000002023-10-25Nonehttps://www.outtvgo.com/details/TV_SHOW/collection/6339796989112/disasterinas-my-drag-is-valid{'average': None}9None<p>Disasterina, star of Sado Psychiatrist and The Boulet Brothers' Dragula, interviews a variety of drag artists to showcase the different styles of drag in performance, looks, and personalities. From seasoned underground fan favorites to the lesser known newbies, Disasterina and her talented guests prove that ALL drag is valid.</p>1728971819{'self': {'href': 'https://api.tvmaze.com/shows/73167'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/3029154', 'name': 'Gothess Jasmin'}}2024-01-31
47472848032https://www.tvmaze.com/episodes/2848032/fox-news-night-2024-01-31-episode-22Episode 22202422.0regular2024-01-3123:002024-02-01T04:00:00+00:0060.000000{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2848032https://api.tvmaze.com/shows/76581Fox News @ Night76581https://www.tvmaze.com/shows/76581/fox-news-nightFox News @ NightNewsenglish[]running60.0000002017-10-30Nonehttps://www.foxnews.com/shows/fox-news-night{'average': None}6{'id': 185, 'name': 'Fox News Channel', 'country': {'name': 'United States', 'code': 'US', 'timezone': 'America/New_York'}, 'officialSite': 'https://www.foxnews.com/'}<p><b>Fox News @ Night</b> is a live hour of hard news and analysis of the most compelling stories from Washington and across the country.</p>1716912888{'self': {'href': 'https://api.tvmaze.com/shows/76581'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2889864', 'name': 'Episode 132'}}2024-01-31
47482751926https://www.tvmaze.com/episodes/2751926/the-tonight-show-starring-jimmy-fallon-2024-01-31-arnold-schwarzenegger-kathryn-newton-the-lemon-twigsArnold Schwarzenegger, Kathryn Newton, The Lemon Twigs202417.0regular2024-01-3123:352024-02-01T04:35:00+00:0060.000000{'average': None}<p>Actor Arnold Schwarzenegger; actress Kathryn Newton; The Lemon Twigs perform.</p>https://api.tvmaze.com/episodes/2751926https://api.tvmaze.com/shows/718The Tonight Show Starring Jimmy Fallon718https://www.tvmaze.com/shows/718/the-tonight-show-starring-jimmy-fallonThe Tonight Show Starring Jimmy FallonTalk Showenglish[Comedy]running60.0000002014-02-17Nonehttp://www.nbc.com/the-tonight-show{'average': 4.4}99{'id': 1, 'name': 'NBC', 'country': {'name': 'United States', 'code': 'US', 'timezone': 'America/New_York'}, 'officialSite': 'https://www.nbc.com/'}<p>Emmy Award and Grammy Award winner Jimmy Fallon brought NBC's "The Tonight Show" back to its New York origins when he launched <b>The Tonight Show Starring Jimmy Fallon </b>from Rockefeller Center. Fallon puts his own stamp on the storied NBC late-night franchise with his unique comedic wit, on-point pop culture awareness, welcoming style and impeccable taste in music with the award-winning house band, The Roots.</p>1730456420{'self': {'href': 'https://api.tvmaze.com/shows/718'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/3038487', 'name': 'Anthony Mackie, Sarah Sherman, Shin Lim'}, 'nextepisode': {'href': 'https://api.tvmaze.com/episodes/3038504', 'name': 'Kevin Kline, Lester Holt, Maddie Wiener'}}2024-01-31